Network diagrams (node-link graphs) have wide scope of applications in almost all domains of science. Any data set that can be modeled as a collection of linked nodes can be represented as a network diagram. In life science, a network diagram can be used as a pathway diagram, protein interaction diagram, signal transduction process, workflow process, and other similar processes. Network diagrams may be used to provide computer-based visualization of computer networks, communications networks, and many other technical systems.
Computer-based visualization of network diagrams involves contributions from many disciplines such as: graph theory, information visualization technology, visual perception, cognitive science, as well as others, to arrive at an efficient representation that exploits human visual processing to reduce the cognitive load of many tasks that require understanding of global or local structures.
While network diagrams may convey necessary information, many times they become more confusing than necessary. For example, in the case of biological diagrams, if a diagram is utilized to illustrate a pathway or interaction diagram, the amount of graphics displayed on the screen may be overwhelming to the user. Further still, by restraining the connecting lines to two dimensions, this may limit the ability of the program to display all connections in a logical or easily perceivable manner.
Many times one line may be drawn over another line, thereby making the diagram visually confusing to the user such that the user, must take time to trace the appropriate line across/down the screen in order to see the connection between the nodes.
Further, while network diagrams may be useful to display an amount of data in a more simplified graphical nature, there are still shortcomings when it is desirable to display more than one set of data at a time. For example, in gene expression, it may be desirable to display multiple tests on a single screen using a network diagram so that the user can determine if any data collected in each test differs in any manner, or to attempt to observe connections among the data. In order to make such diagram displays from which the observations can be made, data values are encoded and the encodings are used to render the network nodes and links, see, e.g., co-owned and currently pending application Ser. No. 10/155,616, filed May 22, 2002 and titled “System and Methods for Visualizing Diverse Biological Relationships”, which is incorporated herein, in its entirety, by reference thereto. It would be desirable to overlay encoded values from other data sets on the nodes to make comparisons between values from different experiments with regard to the same entity represented by a given node. Conventional network diagrams cannot be utilized to display more than one data set because each data set will be written over the other one and/or some portions of each data set may be blocked by a portion of another data set.
Therefore there is a need for improved network diagrams and visualization techniques that can convey visual information to a user in a more simplified manner. There are further needs for providing visualization schemes capable of displaying more than one set of data simultaneously, while still providing easily interpreted readability.
An earlier attempt at presenting graphical detail in a more readable format is available in a product known as “Star Tree Viewer” (available from Inxight Software, Sunnyvale, Calif.), a screen display of which is shown in FIG. 9. Star Tree Viewer provides a technique whereby an entire tree can be kept within the confines of a circular area on a conventional display screen. The Star Tree Viewer renders a tree data structure onto a hyperbolic surface, with the higher level nodes displayed at the center of the display and “branches” of the tree extending radially outwardly therefrom toward the periphery to display lower level nodes, resulting in an appearance of the form shown in FIG. 9. Although Star Tree Viewer provides an interesting view of a hierarchical structure, it is only applicable to tree structures and not to network diagrams or graphs in general.
FIG. 10 shows a view of a product known as “Pop out Prism” (http://www2.parc.com/csl/projects/popoutprism), by Xerox Parc, which provides a Web browser that aids navigation by providing an enhanced thumbnail overview of Web pages. This enhanced thumbnail contains attention-grabbing “popouts” which are generated dynamically based on user input of URLs and keywords. These popouts enable users to immediately locate relevant information in a page. Popout Prism also adds popouts to full Web pages so that users can recognize and locate keywords. This scheme is only suited for textual images, not for graphs.